Applying a Model

Overview

• Can save a trained model.
• Load it and make predictions for new data.
• Rank on predictions and trade (more later).
• Important to interpret the model
  • What combinations of features does it like/dislike?
  • What industries does it like/dislike?

Repeat prior example

• Use roeq and mom12m for 2021-01 as before.
• Predict rnk as before.
• Use a neural net with two hidden layers: 4 neurons in the first and 2 in the second.

Define and fit model

from sklearn.neural_network import MLPRegressor

X = data[["roeq", "mom12m"]]
y = data["rnk"]

model = MLPRegressor(
  hidden_layer_sizes=(4, 2),
  random_state=0
)
model.fit(X,y)